Update app.py

app.py

@@ -1,12 +1,12 @@
 from fastai.vision.all import *
 import gradio as gr
 import glob
+
+import torch
 import timm
 from timm.models import convnext
 convnext_model = 'convnext_tiny_in22k'
 model_architecture=timm.create_model(convnext_model)
-
-import torch
 class FastaiConvNext(torch.nn.Module):
     def __init__(self, original_model):
         super().__init__()
@@ -18,14 +18,7 @@ class FastaiConvNext(torch.nn.Module):
 
 model = FastaiConvNext(model_architecture)
 
-#class Hook():
-#  def hook_func(self, m, i, o): self.stored = o.detach().clone()
-
-#learn = load_learner("resnet152_fit_one_cycle_freeze_91acc.pkl", cpu=True)
-
-#categories = ('arbanasi', 'filibe', 'gjirokoster', 'iskodra', 'kula', 'kuzguncuk', 'larissa_ampelakia', 'mardin', 'ohrid', 'pristina', 'safranbolu', 'selanik', 'sozopol_suzebolu', 'tiran', 'varna')
-
-learn = load_learner("convnext_mixup_0_33.pkl", cpu=True)
+learn = load_learner("convnext_mixup_0_33.pkl")
 categories = ('arbanasi', 'filibe', 'gjirokoster', 'iskodra', 'kula', 'kuzguncuk', 'larissa_ampelakia', 'mardin', 'ohrid', 'pristina', 'safranbolu', 'selanik', 'sozopol_suzebolu', 'tiran', 'varna')
 def classify_img(img):
   pred,idx,probs=learn.predict(img)
@@ -33,9 +26,6 @@ def classify_img(img):
 
 image=gr.inputs.Image(shape=(128,128))
 label=gr.outputs.Label()
-examples_=[]
-for i in glob.glob("valid/**/*.jpg", recursive=True):
-    examples_.append(i)
 
 examples=["filibe-1-1.jpg",
           "ohrid-3-1.jpg",